Token Classification
SpanMarker
Safetensors
English
ner
named-entity-recognition
generated_from_span_marker_trainer
climate-change
earth-science
Eval Results (legacy)
Instructions to use P0L3/CliReNER-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use P0L3/CliReNER-roberta-base with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("P0L3/CliReNER-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f55f4f7d63fccdb0130004e820c91d998faca848abb48e46b9757534c0123c5
- Size of remote file:
- 5.91 kB
- SHA256:
- c6337b7c40ce7b564e665044efefbb24adfa67a39e2ec1d8bb42415bd792d18a
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